Positioning Technology Of Wireless Sensor Network Node Based On The Ratio Of The Number Of Hops

The localization of sensor node is one of significant technologies in Wireless Sensor Networks(WSN), it bases on a few position known nodes then calculate Self-location through a special location mechanism. Because of constraint in storage, computation and battery power, etc. so the research of a location algorithm, which satisfy a appropriate accuracy requirement, has low calculate complexity and traffic load, so that it can decrease power consumption and prolong network lifetime, is essential to WSN application in both theoretical and application areas.At first, we introduce the basic principles, calculate methods and performance evaluation criterion of node location algorithm, analyses the basic ideas, application backgrounds and performance of various existing algorithms. Especially, we did much research on DV-Hop algorithm, that adapts to large scale network, analysed and discussed its characteristics deeply. Considering those drawbacks of DV-Hop, such as high traffic load and position error, we designed an algorithm which does some improvements on DV-Hop. It uses the grid network structure, defines two-grade anchors which have separate communication range to assist positing,the whole process is divided into two stages that a rough location bind and accurate calculation: (1) according to the linear inverse relationship between signal strength node received and the Euclidean distance of two nodes, we can narrow the scope of position and set the filter for the final result. (2) In the narrower scope, we statistic the least hop count between two nodes through network broadcast, and construct Apollonius Circle by hop count ratio, at the end, we use Trilateration and Max Likelihood Estimation to calculate the location.This improved algorithm is realized on MoteWorks 2.0 F and IRIS nodes which are producted by Crossbow company, we tested and compared the results of traffic load, positioning accuracy and edge stability. The experiment shows that, compares to DV-Hop, this algorithm achieves a obvious reduction in network load, a high positioning accuracy and a better edge stability. Meanwhile, it decreases the calculation complexity slightly, gets the goal expected.